Integration of declarative approaches (System Demonstration)

  • Arne Frick
  • Can Keskin
  • Volker Vogelmann
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1190)

Abstract

This demonstration shows the Gold system, an extensible software architecture integrating several declarative layout strategies, including springembedders, local constraints and genetic algorithms. The underlying paradigm is to consider graph layout problems as geometric constraint satisfaction problems

In addition to satisfying global aesthetics criteria, the system allows for the interactive specification of local criteria per vertex (edge).

References

  1. 1.
    F. J. Brandenburg. Designing graph drawings by layout graph grammars. In Roberto Tamassia and Ioannis Tollis, editors, Proceedings of Graph Drawing '94, volume 894 of Lecture Notes in Computer Science, pages 416–427. DIMACS Workshop on Graph Drawing, Springer Verlag, 1995.Google Scholar
  2. 2.
    I. Bruß and A. Frick. Fast interactive 3-D graph visualization. In Franz Brandenburg, editor, Proceedings of Graph Drawing'95, volume 1027 of Lecture Notes in Computer Science, pages 99–110. Springer Verlag, 1996.Google Scholar
  3. 3.
    I. F. Cruz and J. P. Twarog. 3-D graph drawing with simulated annealing. In F. J. Brandenburg, editor, Graph Drawing, volume 1027 of Lecture Notes in Computer Science, pages 162–165. Springer-Verlag, 1995.Google Scholar
  4. 4.
    E. Dengler, M. Friedell, and J. Marks. Constraint-driven diagram layout. In Proceedings of the 1993 IEEE Workshop on Visual Languages, pages 330–335, 1993.Google Scholar
  5. 5.
    J. Holland. Adaptation in Natural and Artificial Systems. University of Michigan Press, 1975.Google Scholar
  6. 6.
    C. Kosak, J. Marks, and S. Shieber. Aparallel genetic algorithm for network-diagram layout. In Proc. 4th Int. Conf. on Genetic Algorithms (ICGA91), 1991.Google Scholar
  7. 7.
    T. Lin and P. Eades. Integration of declarative and algorithmic approaches for layout creation. In R. Tamassia and I. G. Tollis, editors, Graph Drawing, volume 894 of Lecture Notes in Computer Science, pages 376–387. DIMACS, Springer-Verlag, October 1994. ISBN 3-540-58950-3.Google Scholar
  8. 8.
    E. Mäkinen and M. Sieranta. Genetic algorithms for drawing bipartite graphs. Technical report, Department of Computer Science, University of Tampere, 1994.Google Scholar
  9. 9.
    T. Masui. Graphic object layout with interactive genetic algorithms. In Proceedings of the 1992 IEEE Workshop on Visual Languages, pages 74–87, Seattle, Washington, 1992.Google Scholar
  10. 10.
    S. Matsuoka, S. Takahashi, T. Kamada, and A. Yonezawa. A general framework for bidirectional translation between abstract and pictorial data. TOIS, 10(4):408–437, 1992.CrossRefGoogle Scholar
  11. 11.
    Z. Michalewicz. Genetic algorithms + data structures=evolution programs. Springer-Verlag, 1992.Google Scholar
  12. 12.
    Z. Michalewicz and C. Janikow. Handling constraints in genetic algorithms. In R. Belew and L. Booker, editors, Genetic Algorithms, pages 151–157, 1991.Google Scholar
  13. 13.
    Phillips, Levy, and Munzner. Geomview: An interactive geometry viewer. Notices of the American Mathematical Society, 40, 1993.Google Scholar
  14. 14.
    A. Witkin, K. Fleischer, and A. Barr. Energy constraints on parameterized models. In Maureen C. Stone, editor, Computer Graphics (SIGGRAPH '87 Proceedings), volume 21, pages 225–232, July 1987.Google Scholar

Copyright information

© Springer-Verlag 1997

Authors and Affiliations

  • Arne Frick
    • 1
  • Can Keskin
  • Volker Vogelmann
    • 2
  1. 1.Tom Sawyer SoftwareBerkeley
  2. 2.Institut für TelematikUniversität KarlsruheKarlsruheGermany

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